Search: “retrieval”

UniPolicy: Unified Objective-Specific Policies for Generative Search Advertising

model-releasesarxiv-cs-cl

arXiv:2609.20630v1 Announce Type: new Abstract: Search advertising connects user intent with commercial content and plays a critical role in platform monetization. Recent systems typically align pretr

18 Sept 2026

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Research

Beyond Accuracy: How Procedural Traces Shift the Decision Criterion of LLM Overseers

DGX agent

arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed st

researcharxiv-cs-ai

17 Sept 2026

Cognitive Extensions for Dual-Process Language Agents: Memory and Self-Reflection in Interactive Environments

arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro

agentsarxiv-cs-ai

Does AI Assistance Leave a Temporal Fingerprint? Detecting Overreliance in AI-Assisted Writing and Programming

arXiv:2609.17883v1 Announce Type: cross Abstract: The rapid adoption of generative AI has made final artifacts unreliable evidence of student learning, and AI detectors that examine only the finished

Enhancing knowledge tracing robustness for new question cold start in Intelligent Tutoring Systems

arXiv:2512.07179v2 Announce Type: replace Abstract: Intelligent Tutoring Systems (ITS) provide personalized learning paths by diagnosing learners' proficiency. Knowledge Tracing (KT) models play a cen

applicationsarxiv-cs-ai

EviGen: Predictive Evidence Scaffolding for Verifiable Clinical Rationale Generation

arXiv:2609.18852v1 Announce Type: new Abstract: Longitudinal electronic health records (EHRs) capture years of patient history across notes, codes, labs, and procedures, and contain evidence needed to

researcharxiv-cs-cl

Gaze as Evidence for Common Grounding: A Cross-Corpus Analysis of MapTask and MUNDEX

arXiv:2609.18011v1 Announce Type: new Abstract: In collaborative tasks with asymmetric information, participants coordinate their understanding through interaction. We ask whether gaze provides eviden

researcharxiv-cs-cl

HALT: Hallucination Assessment via Log-probs as Time series

arXiv:2602.02888v2 Announce Type: replace-cross Abstract: Hallucinations remain a major obstacle for large language models (LLMs), especially in safety-critical domains. We present HALT (Hallucination

How Calibration Content Shapes Attention-Based Reranking

arXiv:2609.17764v1 Announce Type: new Abstract: Attention-based rerankers score documents by aggregating query-to-document attention and subtracting a null-query calibration pass to remove positional

safetyarxiv-cs-cl

Imitation Learning for Autonomous Driving in CARLA

arXiv:2609.17757v1 Announce Type: new Abstract: Behavioral cloning trains a policy offline on expert demonstrations, but deployment is closed loop: each action affects the observations the policy rece

Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

arXiv:2609.18842v1 Announce Type: new Abstract: The scaling laws hold that a language model grows more capable with more parameters and more training data, and Mixture-of-Experts (MoE) architectures h

Limits of Transfer Learning

arXiv:2006.12694v2 Announce Type: replace-cross Abstract: Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain. Although widely use

Long-Context Demonstration Selection Using State Space Models

arXiv:2609.17888v1 Announce Type: cross Abstract: We study the problem of demonstration selection, which involves selecting a subset of examples for prepending to a query to a language model. This pro

applicationsarxiv-cs-cl

Lumen: Parameter-Efficient Alignment of Pretrained Vision and Language Encoders for Zero-Shot Computational Pathology

model-releasesarxiv-cs-cv

arXiv:2609.17868v1 Announce Type: new Abstract: Pathology vision-language models are commonly built by pretraining or fine-tuning large encoders on paired image-caption data. We asked whether a pathol

Local Ai

Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records

arXiv:2609.17631v1 Announce Type: new Abstract: AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history refer to different states

local-aiarxiv-cs-ai

Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization

arXiv:2603.27526v2 Announce Type: replace Abstract: Protein fitness optimization is a discrete search problem, and the representation used for prediction also determines the neighborhood graph travers

researcharxiv-cs-lg

Local Ai

ReRadar: Robust Radar Global Localization via Rotation-Equivariant Descriptor Learning

arXiv:2609.18092v1 Announce Type: new Abstract: Global localization with scanning millimeter-wave radar remains challenging because place-recognition descriptors often discard spatial structure needed

local-aiarxiv-cs-ro

Hardware

Risk-Aware World Modeling with Flow-Guided Occupancy Evolution for Selective Trajectory Planning in Automated Driving

arXiv:2609.18442v1 Announce Type: new Abstract: Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory. We in

hardwarearxiv-cs-ai

ScienceIDE: Turning World's Scientific Codebase into Agent Learnable Environments

arXiv:2609.19134v1 Announce Type: new Abstract: Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conv

agentsarxiv-cs-cl

Towards Generalizable Deepfake Detection via Real Distribution Bias Correction

arXiv:2603.14005v2 Announce Type: replace Abstract: To generalize deepfake detectors to future unseen forgeries, most existing methods attempt to simulate the dynamically evolving forgery types using

safetyarxiv-cs-cv

Transcribe, Then Reason: Two-Pass Decomposition for Multimodal Review

arXiv:2609.18958v1 Announce Type: cross Abstract: The natural way to review a long recording or document with a multimodal model is to hand it the raw source and ask for a review in one call. We show

Understanding AI Provider Recommendations in Local Service Markets

arXiv:2609.18341v1 Announce Type: cross Abstract: When someone asks an AI assistant which doctor to see or which firm to trust with their savings, the answer is a referral. We audit AI provider recomm

researcharxiv-cs-cl

A Decision-Support Audit Protocol for Supervision Drift in Proxy-Labeled Credit-Risk Prediction

arXiv:2609.16102v1 Announce Type: cross Abstract: Credit-risk models are trained on proxy labels and deployed under temporal and segment change, yet no single transfer metric separates base-rate shift

AI Policies: Help or Hindrance? A Software Developer's Perspective

arXiv:2609.16496v1 Announce Type: cross Abstract: AI policies introduced by software organisations to mitigate LLM-related risks such as sensitive information leaks and unauthorised usage are not usef

Anatomy of Associative Recall in Fixed-State Recurrences: A Matched-State Decomposition, an Interference Wall, and a Curriculum That Breaks It

arXiv:2609.16183v1 Announce Type: cross Abstract: Fixed-state recurrences--linear attention and state-space models--are reported to lag behind attention on associative recall, but whole-architecture c

safetyarxiv-cs-cl

Tutorials

Attention is All You Need Until You Need Retention

arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pape

tutorialsarxiv-cs-ai

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st

Comparative Characterization of KV Cache Management Strategies for LLM Inference

arXiv:2604.05012v2 Announce Type: replace-cross Abstract: Efficient inference with Large Language Models (LLMs) increasingly relies on Key-Value (KV) caches to store previously computed key and value

Competence-Preserving Resume Perturbations Expose Presentation Sensitivity in LLM Screening

arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, an

FlexEE: Self-Speculative and KV-Compatible Early Exiting for Offloading-Aware LLM Inference

arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights

Japanese Stroke LLM Evaluation: A Conversational Benchmark for Safe Stroke Care in Japanese Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.16739v1 Announce Type: new Abstract: Background: Large language models (LLMs) have achieved physician-comparable performance on multiple-choice medical knowledge examinations, but their cap

Local Ai

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

arXiv:2609.17475v1 Announce Type: new Abstract: Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit, a

local-aiarxiv-cs-ai

LSREP: A Longitudinal State-Replay Protocol for Evaluating Conversational Memory, with ICE v2 as an Audited Local-First Architecture

arXiv:2609.16730v1 Announce Type: new Abstract: Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporate

applicationsarxiv-cs-ai

Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation

arXiv:2606.18960v3 Announce Type: replace Abstract: Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experi

safetyarxiv-cs-cv

Multi-Agent Collaboration for Automated Design Exploration on High Performance Computing Systems

arXiv:2603.11515v2 Announce Type: replace Abstract: Today's scientific challenges, from climate modeling to Inertial Confinement Fusion design to novel material design, require exploring huge design s

NepKANUN: A RAG-Based Nepali Legal Assistant

arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as

applicationsarxiv-cs-cl

QALPA: Property-guided diffusion modeling for efficient exploration of chemical spaces of flexible molecules

arXiv:2609.16527v1 Announce Type: cross Abstract: Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with

Robustness as an Emergent Property of Task Performance

arXiv:2602.03344v2 Announce Type: replace-cross Abstract: Robustness is widely viewed as a key challenge for real-world applications. However, because current research focuses only on difficult tasks,

applicationsarxiv-cs-ai

Safe Error Correction for Language Models: Frozen-Base Adjustment with Capability Preservation

arXiv:2609.16145v1 Announce Type: new Abstract: We study a practical question: can a small correction module fix errors in a frozen language model's outputs without degrading its base capabilities? We

SciNLP: A Domain-Specific Benchmark for Full-Text Scientific Entity and Relation Extraction in NLP

model-releasesarxiv-cs-cl

arXiv:2509.07801v5 Announce Type: replace Abstract: Structured information extraction from scientific literature is crucial for capturing core concepts and emerging trends in specialized fields. While

Spurious Tool Use: When RL Agents Learn the Wrong Reason to Act

arXiv:2609.16268v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly interleave natural language reasoning with external tools such as web search and code execution. These to

safetyarxiv-cs-cl

A Generative AI Integrated Multimodal Framework for Low-Latency Multi-Camera Person Re-Identification

arXiv:2609.14419v1 Announce Type: cross Abstract: Person re-identification (ReID) is essential for multi-camera surveillance and tracking, yet remains difficult due to viewpoint and illumination chang

A Unified Vision-Language Model for PSMA PET/CT Report Generation, Visual Question Answering, and Lesion Segmentation

arXiv:2609.15603v1 Announce Type: cross Abstract: Accurate PSMA PET/CT interpretation is central to prostate cancer management, yet existing PET/CT AI models typically address isolated tasks. We propo

safetyarxiv-cs-ai

Are LLMs Good Financial User Simulators? A Preliminary Study

arXiv:2609.15727v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as user simulators, but their ability to reproduce evolving individual financial decisions remains un

Automating Attack Graph Construction for Agentic Pentesting. Towards Neuro-Symbolic Vulnerability Hunting

arXiv:2609.15523v1 Announce Type: cross Abstract: Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic framew

agentsarxiv-cs-ai

Beyond OCR Accuracy: Text-Centric VQA Under Image Degradation with Modular and End-to-End

arXiv:2609.13815v1 Announce Type: new Abstract: Text-centric Visual Question Answering (VQA) requires reading and reasoning over text embedded in images, a task made substantially harder when images s

applicationsarxiv-cs-cv

Carryover Drafting: Recycling Rejected States for Speculative Decoding

arXiv:2609.14717v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by verifying multiple drafted tokens in parallel, allowing a single target forward pass to accept sever

Cost Characterization of Vertically Partitioned Federated Knowledge Graphs

arXiv:2609.13664v1 Announce Type: new Abstract: Knowledge graphs are increasingly distributed across autonomous organizations that share an entity space but own disjoint subsets of relations, forming

agentsarxiv-cs-ai